Methods and Devices for Improving Indicia Decoding with an Imaging Device

ABSTRACT

Methods and devices for improving indicia decoding with an imaging device are disclosed herein. An example method includes: (a) searching, by an imaging device, a search region within a current image for an indicia, wherein the search region includes a plurality of search seeds; (b) attempting, by the imaging device, to decode the indicia within the search region by analyzing image data corresponding to each seed of the plurality of search seeds; (c) responsive to not decoding the indicia, capturing, by the imaging device, a subsequent image featuring the indicia; (d) adjusting, by the imaging device, the search region based on a distance between the imaging device and the indicia featured in the subsequent image; (e) designating the subsequent image as the current image; and (f) iteratively performing (a)-(f) until the imaging device decodes the indicia.

BACKGROUND

Barcode scanning devices have provided reliable product identificationand tracking in many industries for decades. While such conventionalscanning devices are capable of detecting and decoding indicia at shortdistances, these capabilities suffer as the distance of the indicia fromthe device increases and the relative size of the indicia within theimage decreases. Namely, these conventional scanning devices maygenerally be capable of detecting and decoding indicia of a certainrelative size within a captured image, but relatively small indicia maynot always be detected and decoded. Users of these scanning devices mayhold the device at a variety of distances when attempting to detect anddecode an indicia, and as a result, may place the indicia far enoughfrom the device that the indicia is too small within the captured imagefor the device to successfully detect and decode it. As a result, usersmay unintentionally fail to scan an indicia, as the device may be unableto detect and decode the indicia, despite being within the scannablerange of the device.

Failing to detect and decode indicia can result in unidentified productsand products that are not tracked as part of shipments, leading todelayed or missing shipments. Moreover, the conventional indiciascanning device may occupy significant amounts of processing resourcesand time when searching a relatively large search region for the smallindicia. When the conventional indicia scanning device fails to detectand decode the indicia, subsequent images may be required, and thesearch process may begin again, thereby further wasting preciousprocessing resources and time. Overall, failing to detect and decodeindicia reduces efficiency and increases the time required to resolveissues related to products that have not been identified/tracked throughsuccessful indicia detection and decoding.

Accordingly, there is a need for methods and devices for improvingindicia decoding with an imaging device.

SUMMARY

In one embodiment, the present invention is a method for improvingindicia decoding with an imaging device. The method comprises: (a)searching, by an imaging device, a search region within a current imagefor an indicia, wherein the search region includes a plurality of searchseeds; (b) attempting, by the imaging device, to decode the indiciawithin the search region by analyzing image data corresponding to eachseed of the plurality of search seeds; (c) responsive to not decodingthe indicia, capturing, by the imaging device, a subsequent imagefeaturing the indicia; (d) adjusting, by the imaging device, the searchregion based on a distance between the imaging device and the indiciafeatured in the subsequent image; (e) designating the subsequent imageas the current image; and (f) iteratively performing (a)-(f) until theimaging device decodes the indicia.

In a variation of this embodiment, adjusting the search region furtherincludes reducing or increasing an area of the search region based onthe distance.

In another variation of this embodiment, adjusting the search regionfurther includes increasing or decreasing a number of search seedswithin the search region based on the distance.

In yet another variation of this embodiment, a center of an aimingindicator is disposed in a center of the search region and the indiciais presumed to be at the center of the aiming indicator.

In still another variation of this embodiment, the indicia is a barcode,and the method further comprises: attempting to decode the barcodewithin the search region by applying a decoding algorithm to the imagedata from each seed.

In yet another variation of this embodiment, after each iteration, theimaging device increases an iteration index, and the method furthercomprises: (f) iteratively performing (a)-(f) until the imaging devicedecodes the indicia or at least one of (i) the imaging device determinesthat the iteration index exceeds an iteration index threshold, (ii) theimaging device determines that a decoding time corresponding to thecurrent image exceeds a decoding time threshold, or (iii) the image datafrom each seed in the plurality of search seeds is analyzed withoutdetecting the indicia. Further in this variation, and responsive to theimaging device determining that the iteration index exceeds theiteration index threshold, the decoding time exceeds the decoding timethreshold, or the image data is analyzed without detecting the indicia,the method further comprises: displaying, by the imaging device, amessage to a user requesting another image featuring the indicia.

In still another variation of this embodiment, each seed of theplurality of search seeds is randomly placed within the search region.

In another embodiment, the present invention is an imaging device forimproving indicia decoding. The device comprises: an imaging assemblyconfigured to capture a current image featuring an indicia, the currentimage comprising a set of image data; one or more processors; and anon-transitory computer-readable memory coupled to the imaging assemblyand the one or more processors, the memory storing instructions thereonthat, when executed by the one or more processors, cause the one or moreprocessors to: (a) search a search region within the image for theindicia, wherein the search region includes a plurality of search seeds,(b) attempt to decode the indicia within the search region by analyzingimage data from the set of image data that corresponds to each seed ofthe plurality of search seeds, (c) responsive to not decoding theindicia, cause the imaging assembly to capture a subsequent imagefeaturing the indicia, (d) adjust the search region based on a distancebetween the imaging device and the indicia featured in the subsequentimage, (e) designate the subsequent image as the current image, and (f)iteratively perform (a)-(f) until the indicia is decoded.

In a variation of this embodiment, the instructions, when executed bythe one or more processors, further cause the one or more processors to:adjust the search region by reducing or increasing an area of the searchregion based on the distance.

In another variation of this embodiment, the instructions, when executedby the one or more processors, further cause the one or more processorsto: adjust the search region by increasing or decreasing a number ofsearch seeds within the search region based on the distance.

In yet another variation of this embodiment, the imaging device furthercomprises: a distance calculator configured to calculate the distancebetween the imaging device and the indicia based on an aiming indicatorthat is centered on the indicia.

In still another variation of this embodiment, the indicia is a barcode,and the instructions, when executed by the one or more processors,further cause the one or more processors to: attempt to decode thebarcode within the search region by applying a decoding algorithm to theimage data corresponding to each seed.

In yet another variation of this embodiment, after each iteration, theone or more processors increase an iteration index, and theinstructions, when executed by the one or more processors, further causethe one or more processors to: (f) iteratively perform (a)-(f) until theindicia is decoded or at least one of (i) the one or more processorsdetermine that the iteration index exceeds an iteration index threshold,(ii) the one or more processors determine that a decoding timecorresponding to the current image exceeds a decoding time threshold, or(iii) the image data from each seed in the plurality of search seeds isanalyzed without detecting the indicia. Further in this variation, theinstructions, when executed by the one or more processors, further causethe one or more processors to: responsive to determining that theiteration index exceeds the iteration index threshold, the decoding timeexceeds the decoding time threshold, or the image data is analyzedwithout detecting the indicia, display a message to a user requestinganother image featuring the indicia.

In yet another embodiment, the present invention is a tangiblemachine-readable medium comprising instructions for improving indiciadecoding, when executed, cause a machine to at least: A tangiblemachine-readable medium comprising instructions for improving indiciadecoding, when executed, cause a machine to at least: (a) search asearch region within a current image for an indicia, wherein the searchregion includes a plurality of search seeds; (b) attempt to decode theindicia within the search region by analyzing image data thatcorresponds to each seed of the plurality of search seeds; (c)responsive to not decoding the indicia, capture a subsequent imagefeaturing the indicia; (d) adjust the search region based on a distancefrom the indicia featured in the subsequent image; (e) designate thesubsequent image as the current image; and (f) iteratively perform(a)-(f) until the indicia is decoded.

In a variation of this embodiment, the instructions, when executed,further cause the machine to at least: adjust the search region byreducing or increasing an area of the search region based on thedistance.

In another variation of this embodiment, the instructions, whenexecuted, further cause the machine to at least: adjust the searchregion by increasing or decreasing a number of search seeds within thesearch region based on the distance.

In yet another variation of this embodiment, the indicia is a barcode,and the instructions, when executed, further cause the machine to atleast: attempt to decode the barcode within the search region byapplying a decoding algorithm to the image data corresponding to eachseed.

In still another variation of this embodiment, after each iteration, theinstructions, when executed, further cause the machine to at leastincrease an iteration index, and: (f) iteratively perform (a)-(f) untilthe indicia is decoded or at least one of (i) the iteration indexexceeds an iteration index threshold, (ii) a decoding time correspondingto the current image exceeds a decoding time threshold, or (iii) theimage data from each seed in the plurality of search seeds is analyzedwithout detecting the indicia; and responsive to determining that theiteration index exceeds the iteration index threshold, the decoding timeexceeds the decoding time threshold, or the image data is analyzedwithout detecting the indicia, display a message to a user requestinganother image featuring the indicia.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying figures, where like reference numerals refer toidentical or functionally similar elements throughout the separateviews, together with the detailed description below, are incorporated inand form part of the specification, and serve to further illustrateembodiments of concepts that include the claimed invention, and explainvarious principles and advantages of those embodiments.

FIG. 1 is a perspective view of an example imaging device, in accordancewith various embodiments of the present invention.

FIG. 2A illustrates an example prior art search region within a field ofview (FOV) of an imaging device.

FIG. 2B illustrates a portion of the example prior art search region ofFIG. 2A that is centered on the indicia.

FIG. 3A illustrates an example search region within a field of view(FOV) of an imaging device that has a reduced search region size and anincreased search seed density relative to the example prior art searchregion of FIG. 2A, in accordance with various embodiments of the presentinvention.

FIG. 3B illustrates a portion of the example search region of FIG. 3Athat is centered on the indicia, in accordance with various embodimentsof the present invention.

FIG. 4 is a block diagram representative of an example logic circuit forimplementing the example imaging device of FIG. 1 , in accordance withembodiments described herein.

FIG. 5 illustrates a method for improving indicia decoding with animaging device, in accordance with various embodiments of the presentinvention.

Skilled artisans will appreciate that elements in the figures areillustrated for simplicity and clarity and have not necessarily beendrawn to scale. For example, the dimensions of some of the elements inthe figures may be exaggerated relative to other elements to help toimprove understanding of embodiments of the present invention.

The apparatus and method components have been represented whereappropriate by conventional symbols in the drawings, showing only thosespecific details that are pertinent to understanding the embodiments ofthe present invention so as not to obscure the disclosure with detailsthat will be readily apparent to those of ordinary skill in the arthaving the benefit of the description herein.

DETAILED DESCRIPTION

Generally speaking, users of imaging devices configured to detect anddecode scannable indicia desire that the imaging devices successfullydetect and decode scannable indicia at any suitable range from thedevice. When an indicia is far from the scanning device, it appearssmall in the captured image, and correspondingly occupies a smallportion of the search region. Conventional indicia scanning devicessearch over a relatively large search region for such a small indicia,thereby wasting substantial amounts of time. To further complicatematters, when the indicia itself is relatively small (e.g., smallbarcodes), then conventional indicia scanning devices struggleconsiderably to detect them due to the significantly decreasedprobability of detection relative to larger indicia. Accordingly,conventional indicia scanning devices suffer from a lack of consistent,reliable indicia detection and decoding capabilities when the indiciaoccupies a relatively small portion of the captured image.

The methods/device of the present disclosure provide solutions to thisindicia detection and decoding problem associated with traditionalscanning devices. Namely, the methods/devices of the present disclosurealleviate these problems associated with traditional scanning devices byintroducing an adjustable search region within images captured by animaging device. The search region may include a plurality of searchseeds that each include data that may enable the imaging device todetect and decode an indicia. If the imaging device is initiallyunsuccessful when attempting to detect/decode the indicia featured in animage, the imaging device may iteratively capture a subsequent image andadjust the search region based on a distance between the imaging deviceand the indicia featured in the subsequent image until the imagingdevice successfully decodes the indicia. Generally speaking, the searchseeds may correspond to areas within a captured image (e.g., 5 pixels by5 pixels) that include image data to be analyzed by an indicia decoder.In some instances, the image data contained within an area representedby a search seed may include image data associated with an indiciarepresented within the captured image. Thus, by analyzing the image datacorresponding to each search seed, the imaging device may detect anddecode the indicia represented within the captured image.

As a result, the methods/devices of the present disclosure generallyimprove the successful detection and decoding rates of indicia byimaging devices. These improvements may result in a significantreduction in the number of unidentified products and products that arenot tracked as part of shipments, resulting in fewer delayed or missingshipments. Thus, the methods/devices of the present disclosure maygenerally increase efficiency and decrease the overall time required toresolve issues related to products that have not been identified/trackedthrough successful indicia detection and decoding.

Referring now to the drawings, FIG. 1 is a perspective view 100 of anexample imaging device 100, in accordance with various embodiments ofthe present invention. The example imaging device 100 includes anexample housing 102 in which an imaging assembly 106 is disposed. Theimaging assembly 106 captures image data representing a target in afield of view (FOV) 108 at least partially defined by a front-facingopening or window 110 (also referenced herein as an “optical window”) ona front side 112 of the example imaging device 100. The example imagingdevice 100 includes an indicia decoder 114 in communication with theimaging assembly 106, and configured to receive the image data anddetect/decode an indicia captured in the image data.

The example housing 102 of FIG. 1 includes a generally elongated handleor lower handgrip portion 116, and an upper body portion 118 having thefront side 112 at which the front-facing opening or window 110 islocated. The cross-sectional dimensions and overall size of the handgripportion 116 are such that the example imaging device 100 can beconveniently held in an operator's hand during operation. Thefront-facing opening or window 110 is configured to face generally awayfrom a user when the user has the example imaging device 100 in ahandheld position. The portions 116 and 118 may be constructed of alightweight, resilient, shock-resistant, self-supporting material, suchas a synthetic plastic material. The housing 102 may be injectionmolded, but can also be vacuum-formed or blow-molded to form a thinhollow shell which bounds an interior space whose volume is sufficientto contain the various components of the handheld scanner 100. Althoughthe housing 102 is illustrated as a portable, point-of-transaction,gun-shaped, handheld housing, any other configuration including ahands-free configuration could be used.

A manually actuatable trigger 120 is mounted in a moving relationship onthe handgrip portion 116 in a forward facing region 124 of the handgripportion 116. An operator's finger can be used to actuate (e.g., depress)the trigger 120 once a target falls within the imaging field of view 108to cause the imaging assembly 106 to capture an image of the target. Asa result of actuating the trigger 120, the example imaging device 100may generate an aiming indicator 109. The aiming indicator 109 mayvisually indicate the FOV 108 of the example imaging device 100 for theoperator utilizing the device 100, and may more specifically indicate aregion within the FOV 108 where the device 100 may successfullydetect/decode and/or otherwise interpret an indicia within the FOV 108.As such, the aiming indicator 109 may generally guide an operator toplace an indicia in the correct location within the FOV 108 to optimizethe likelihood of successful detection and decoding of the indicia bythe indicia decoder 114. Moreover, as discussed herein, the aimingindicator 109 may be utilized by the distance calculator 123 in order tocalculate distances between the imaging device 100 and the indicia.These distances may then be used on an image-by-image basis to determinehow the search region generator 122 should adjust the search region toincrease the likelihood of successful indicia detection/decoding withoutunnecessarily increasing the overall processing burden of the imagingdevice 100.

Accordingly, the example imaging device 100 may include a search regiongenerator 122 that is configured to generate and update/adjust an areaaround a center of the aiming indicator 109 (also referenced herein as a“search region”) as well as generating search seeds (not shown) withinthe search region to enable the indicia decoder 114 to detect and decodean indicia (not shown) within the portion of the FOV 108 defined by theindicator 109. Generally, the search region generator 122 may designatea region around the aiming indicator 109 as the search region, which thegenerator 122 may then randomly populate with search seeds. If the imagedata contained in the areas of the search region represented by thesearch seeds are insufficient to detect and/or decode an indiciafeatured in a captured image, then the search region generator 122 mayiteratively capture subsequent images and update/adjust the size of thesearch region and/or the search seed density within the search regionbased on a distance between the imaging device 100 and the indiciafeatured in the subsequent images (e.g., as calculated by the distancecalculator 123), in order to ensure a successful detection and decodingof the indicia featured within the captured images (e.g., an initialcaptured image and any subsequent images featuring the indicia).

To illustrate, assume that the imaging device 100 captured an imagefeaturing an indicia, the search region generator 122 generated a searchregion with multiple search seeds, but the indicia decoder 114 wasunable to detect and/or decode the indicia utilizing the image data fromthe search seeds within the search region. In this example, the imagingdevice 100 may capture a subsequent image featuring the indicia, and thedistance calculator 123 may determine a distance from the imaging device100 to the indicia featured in the subsequent image. As part ofcalculating the distance to the indicia in the subsequent image, thedistance calculator 123 may determine that the imaging device 100 wasrelatively further from the indicia (e.g., far from the target objectfeaturing the indicia in the captured image) than the imaging device wasin the prior image, from which, the indicia was not successfullydecoded.

Continuing the prior example, and as one example in this circumstance,the search region generator 122 may reduce the size of the search regioncorresponding to the subsequent image relative to the size of the searchregion in the prior image, and may simultaneously generate more searchseeds within the smaller search region in order to more densely populatethe search region with search seeds, thereby increasing the likelihoodof a successful indicia detection and decoding. As another example, thesearch region generator 122 may simply reduce the size of the searchregion without increasing the number of search seeds generated withinthe search region, and as a result, may still increase the search seeddensity within the smaller search region relative to the prior, largersearch region of the prior image that the generator 122 initiallygenerated.

In certain instances, the search region in which the search regiongenerator 122 generates search seeds may be identical to the area withinthe FOV 108 defined by the aiming indicator 109, and/or may be anysuitable size relative to the aiming indicator 109. Moreover, the searchregion and/or the search seeds generated by the search region generator122 may not be visually displayed to a user as a result of actuating thetrigger 120.

In some aspects, the imaging device 100 may include a search seedgeneration function (also referenced herein as a “Picklist” function) inorder to enable the search region generator 122 to generate searchseeds. When an operator selects/enables the Picklist function, theimaging device 100 may activate the search region generator 122 togenerate search seeds within the search region of a captured image,where the center of the aiming indicator 109 may define the center ofthe search region, upon operator actuation of the trigger 120. Forexample, the Picklist function may be a selectable option from a list ofselectable options provided to an operator at the imaging device 100,and/or the Picklist function may be associated with a button, switch,and/or any other physically actuatable object located on the imagingdevice 100.

In certain aspects, the search region generator 122 may randomlygenerate each search seed within the search region of the FOV 108 aroundthe aiming indicator 109. The search region generator 122 may alsorandomly provide a particular search seed density within the searchregion in order to enable the indicia decoder 114 to detect and decodean indicia. Further, the search region generator 122 may generatedifferent numbers/densities/placements of search seeds within the searchregion during a prolonged (e.g., continuous) actuation and/or duringmultiple successive actuations of the trigger 120 as part of aniterative process configured to detect and decode an indicia, asdescribed herein. However, it should be appreciated that the searchregion generator 122 may generate search seeds in any suitable manner.

The imaging device 100 may also include a distance calculator 123 thatis configured to determine a distance between the imaging device 100 anda target object. For example, the distance calculator 123 may utilizeparallax measurements to determine the distance between the imagingdevice 100 and the target object. Any particular indicia may have wellknown and/or otherwise predefined dimensions, such that once an indiciais identified within an image, the distance calculator 123 may utilizethese dimensions of the indicia located within the image to calculatethe distance between the imaging device 100 and the target object basedon parallax. In particular, as the target object, and by association,the indicia is moved further away from the imaging device 100, theperceived size of the indicia may decrease within the FOV 108. Thus, asa general description, the distance calculator 123 may determine theperceived dimensions of the indicia within the captured image, comparethose perceived dimensions to the known dimensions of the indicia, andcalculate a distance between the imaging device 100 and the targetobject.

As another example, the distance calculator 123 may measure the timetaken for a pulse of light to travel from the imaging device 100 to thetarget object and then back to the imaging device 100. Additionally, oralternatively, the distance calculator 123 may utilize the aimingindicator 109 to measure the distance between the imaging device 100 andthe target object containing the indicia presumed to be at the center ofthe aiming indicator 109. Regardless, the distance calculator 123 mayperform these calculations upon actuation of the trigger 120 and/or atany other suitable time before, during, or after the capture of an imageof the target object featuring an indicia.

In any event, once the operator has actuated the trigger 120, and theimaging device 100 has generated the aiming indicator 109, the operatormay then adjust the orientation of the example imaging device 100 untilthe aiming indicator 109 is centered over an indicia included as part ofthe target. The example imaging device 100 may then capture image dataof the target using the imaging assembly 106, the distance calculator123 may determine a distance between the imaging device 100 and theindicia featured in the captured image, and the imaging device 100 maythereafter proceed to detect and decode any indicia included within theimage by applying the indicia decoder 114 to the image data, and morespecifically, to the image data included within the search seedsgenerated by the search region generator 122.

To provide a better understanding of the adaptive search regionfunctionalities of the present disclosure, discussed in reference toFIG. 1 , FIG. 2A illustrates an example prior art search region 202within a FOV 203 of an imaging device. The example prior art searchregion 202 may be centered around an aiming indicator 209, and mayinclude multiple search seeds 204. Each search seed 204 may generallycorrespond to a miniature region within the FOV 203 (and moreparticularly, within the example prior art search region 202) where theimage data contained within each search seed 204 may include dataassociated with a truncated indicia 206. However, the search seeds 204may not be visually generated as a result of an operator actuating atrigger, so it is to be appreciated that the image representing the FOV203 in FIG. 2A may include the search seeds 204 after the imaging devicehas captured image data comprising the image.

Regardless, as illustrated in FIG. 2A, the example prior art searchregion 202 may include a random arrangement of search seeds 204. Whenthe search seeds 204 are generated, the imaging device may analyze imagedata associated with each/some of the search seeds 204 in order todetect and/or decode the truncated indicia 206. However, the imagingdevice that captured this example prior art search region 202 does notinclude the distance calculator 123 and search seed generator 122 ofFIG. 1 , and as a result, the search seed density in the example priorart search region 202 is relatively low considering the small size ofthe indicia 206. Accordingly, such a low search seed density leads to arelatively low possibility of decoding the indicia 206 when compared toa search region with a comparatively higher search seed density (e.g.,example search region 302).

The truncated indicia 206 may have a portion of the top, bottom, sides,middle, and/or any other suitable portion of the indicia 206 blockedand/or otherwise obscured within the FOV 108, such that the regionoccupied by the truncated indicia 206 within the FOV 108 may berelatively small. As a result, the truncated indicia 206 within therelatively large example prior art search region 202 can pose a problemfor the prior art imaging device, because the number of search seeds 204and the overall density of the search seeds 204 may be substantiallysparse, such that the rate of successfully detecting and decoding thetruncated indicia 206 is very low. In particular, a central searchregion portion 208 that includes the truncated indicia 206 illustrateshow minimal the information available to the prior art imaging devicemay be within the relatively large example prior art search region 202.

FIG. 2B illustrates the central search region portion 208 in greaterdetail, and shows how only a few search seeds 204 are located on thetruncated indicia 206. In fact, an overwhelming majority of the searchseeds 204 failed to fall on the truncated indicia 206, such that thesenon-indicia seeds (referenced collectively as 204 a) do not provideuseable information to the prior art imaging device in order to detector decode the truncated indicia 206. By contrast, the indicia seeds(referenced collectively as 204 b) may provide useful image datacorresponding to the truncated indicia 206, but the useful image dataderived from the indicia seeds 204 b may still be insufficient toaccurately detect and/or decode the truncated indicia 206.

It should be appreciated that any single search seed that is locatedwithin and/or contacting an indicia in a captured image may providesufficient image data for the imaging device 100 (e.g., indicia decoder114) of FIG. 1 to successfully detect and/or decode the indicia.However, having only one or a few search seeds contacting an indiciafeatured in a captured image may generally be insufficient for adetection algorithm to accurately and reliably detect and decode theindicia. Accordingly, an effective method to ensure accurate andreliable detection and decoding using such a detection algorithm whenthe imaging device 100 is relatively far from the indicia is to adjustthe search region by increasing/decreasing the size of the search regionand/or increasing/decreasing the number of search seeds contactingand/or located within the indicia featured in the captured image.

Moreover, it should be understood that while most of the aspectsdescribed herein refer to adjusting the search region by decreasing thesize of the search region and/or increasing the search seed density, thetechniques of the present disclosure may also include adjusting thesearch region by increasing the size of the search region, decreasingthe search seed density, and/or keeping one or both values fixed. Forexample, when the distance calculator 123 determines that the imagingdevice 100 is relatively closer to an indicia compared to a prior imagecapture, the search region generator 122 may adjust the search region byincreasing the size of the search region and/or decreasing the searchseed density. Additionally, if the distance calculator 123 determinesthat the imaging device 100 is at a relatively similar distance from theindicia compared to a prior image capture, the search region generator122 may adjust the search region by keeping the size of the searchregion and/or the search seed density constant, and may proceed togenerate a different random assortment of search seeds in order topotentially analyze more/better image data corresponding to the indiciato achieve successful detection/decoding.

In any event, the devices and methods of the present invention mayimprove over these prior art methods by adjusting a search region by,for example, decreasing the search region size and increasing the searchseed density within the search region based on the distance calculator123 calculating a distance between the imaging device and the indicia.To illustrate, FIG. 3A provides an example search region 302 within theFOV 108 of an imaging device (e.g., imaging device 100) that has areduced search region size and an increased search seed density relativeto the example prior art search region 202 of FIG. 2A, in accordancewith various embodiments of the present invention. The example searchregion 302 may be decreased in size relative to the example searchregion 202 by a predetermined amount (e.g., reduced in size by a fixedpercentage or other amount), but it should be understood that the searchregion generator 122 may actively determine the reduced dimensions ofthe example search region 302 in real-time based on the distance betweenthe imaging device and the indicia calculated by the distance calculator123. This decreased size of the example search region 302 and/orincreased search seed density relative to the example prior art searchregion 202 increases the overall likelihood of successfuldetection/decoding of the truncated indicia 206 relative to prior artsystems, thereby decreasing the amount of wasted and/or otherwiseexpended processing time and resources attempting to decode indiciawithin captured images.

As an example, if no search seeds generated by the search regiongenerator 122 included image data sufficient to decode the indicia 206,then the imaging device 100 may capture a subsequent image featuring theindicia 206, and the distance calculator 123 may determine a newdistance between the imaging device 100 and the indicia 206. If theimaging device 100 determines, based on the new distance, that thedevice 100 is further from the indicia than in the prior image, then thegenerator 122 may adjust the search region by decreasing the size of thesearch region by a significant amount (e.g., to example search region302) to focus primarily on the region surrounding the center of theaiming indicator 109.

More specifically, the search region generator 122 may automaticallyadjust the size and search seed density of the search region based onthe new distance between the imaging device 100 and indicia 206calculated by the distance calculator 123, as well as a presumption thatthe operator has positioned the center of the aiming indicator 109 overthe truncated indicia 206. Additionally, the search region generator 122may decrease the dimensions of the search region 302 when the distancecalculator 123 determines that the target object featuring the truncatedindicia 206 is at a relatively larger distance from the imaging device100 than in a prior image. As a result, the example search region 302 isrelatively smaller than the example prior art search region 202 becausethe imaging device 100 has intelligently/actively sized the searchregion 302 and the corresponding search seed density based on thedistance between the imaging device 100 and the indicia 206.

As an example, assume that the example prior art search region 202 hasdimensions of 100 pixels by 100 pixels and a search seed density of 1search seed per 10 pixels as the result of a standardized search regionsize and search seed density generated after each image capture of aprior art imaging device, regardless of the distance between the priorart imaging device and the indicia. Accordingly, when the prior artimaging device analyzes the example prior art search region 202, theprior art device is substantially unlikely to successfully detect/decodethe indicia 206. By contrast, the imaging device 100 of FIG. 1 maycapture an image representative of the FOV 108, the distance calculator123 may determine a distance between the imaging device 100 and thetarget object containing the indicia 206, and the search regiongenerator 122 may generate the search region 302 over the imagerepresented by the FOV 108 with dimensions of 50 pixels by 50 pixels.The search region generator 122 may also populate the example searchregion 302 with the search seeds 304 at a search seed density of 1search seed per 3 pixels, and as a result, the indicia decoder 114 has asignificantly increased likelihood of successfully detecting/decodingthe indicia 206 because the search region 302 and search seed densityare intelligently/actively determined based on the distance from theimaging device 100 to the target object featuring the indicia 206.

However, in some aspects, the search region generator 122 may alsoadjust the search region 302 by increasing the size of the search region302 in response to the distance calculator 123 determining that theimaging device is at a relatively shorter distance from the targetobject than in a prior image capture, such that the truncated indicia206 occupies a relatively larger portion of the subsequently capturedimage. Moreover, when the search region generator 122 increases the sizeof the search region 302, the generator 122 may also decrease the searchseed density within the search region 302 to minimize the amount ofprocessing time required to decode such a large indicia. Extra searchseeds for such a large indicia may not create an increased likelihoodthat the indicia decoder 114 successfully decodes the indicia, as theindicia may be not decodable for other reasons unrelated to search seeddensity (e.g., blurriness, indicia degradation, etc.). Thus, decreasingthe search seed density in such a scenario may optimize the processingtime required to either decode the indicia or determine that the indiciais simply not decodable.

In this manner, the search region generator 122 may determine an optimalsize of and/or search seed density within the search region 302 in orderto detect and/or decode the indicia 206 present within the capturedimage, regardless of whether the target object is far from the imagingdevice 100 or very close to the imaging device. As previously mentioned,each search seed represents a set of image data to be analyzed, and as aresult, each seed generated by the search region generator 122represents additional processing time for the imaging device 100.Decreasing the size of the search region 302 and simultaneouslyincreasing the search seed density for distant, difficult-to-detectindicia increases the overall likelihood of successful detection anddecoding, thereby avoiding subsequent image captures and additionalwasted processing time. Increasing the size of the search region 302 andsimultaneously decreasing the search seed density for close,easy-to-detect indicia increases processing efficiency by avoidinganalysis of unnecessary search seeds. Thus, the search region generator122 may maximize processing efficiency and the likelihood of successfulindicia detection/decoding regardless of whether the target objectfeaturing the indicia is relatively far or near to the imaging device100.

Regardless, the example search region 302 may include a randomarrangement of search seeds 304, as generated by the search regiongenerator 122 of FIG. 1 . When the search region generator 122 hasgenerated the search seeds 304, the imaging device 100 may analyze imagedata associated with each/some of the search seeds 304 in order todetect and/or decode the truncated indicia 206. As previously mentioned,the image captured by the imaging device 100 (e.g., imaging assembly106) may be a grayscale image, such that the image data included in theregions represented by the search seeds 304 may include grayscalevalues. Thus, the imaging device 100 may analyze the grayscale values ofthe regions represented by the search seeds 304 to determine whether ornot any of the regions of the image represented by the search seeds 304include all or a portion of the truncated indicia 206.

Moreover, the image captured by the imaging assembly 106 may be agrayscale image, and the indicia decoder 114 may include a decodingalgorithm (e.g., an edge detection algorithm) configured to analyze thegrayscale image data to determine the presence of and/or decode thetruncated indicia 206. The indicia decoder 114 may receive the grayscaleimage, and may utilize the grayscale image data included in the searchseeds 304 to attempt to detect, for example, edges that are indicativeof the truncated indicia 206. If the indicia decoder 114 is able todetect one or more edges that are indicative of the truncated indicia206, the decoder 114 may also proceed to attempt to decode the truncatedindicia 206 based on the grayscale image data.

As previously mentioned, the truncated indicia 206 may have a portion ofthe top, bottom, sides, middle, and/or any other suitable portion of theindicia 206 blocked and/or otherwise obscured within the FOV 108, and asa result, the region occupied by the indicia 206 within the FOV 108 maybe relatively small. However, the truncated indicia 206 poses less of aproblem within the example search region 302, relative to the exampleprior art search region 202, because the number of search seeds 304 andthe overall density of the search seeds 304 provides a higher likelihoodof detection and decoding of the truncated indicia 206 relative to theexample prior art search region 202. In particular, a central searchregion portion 308 that includes the truncated indicia 206 illustrateshow the information available to the imaging device 100 within thecentral search region portion 308 may be substantially increasedrelative to the central search region portion 208, thereby providing theindicia decoder 114 a much higher likelihood of a successful detectionand decoding of the truncated indicia 206.

FIG. 3B illustrates the central search region portion 308 in greaterdetail, and shows how many of the search seeds 304 are located on thetruncated indicia 206. In fact, a significant number of the search seeds304 were placed on the truncated indicia 206 by the search regiongenerator 122, but the non-indicia seeds (referenced collectively as 304a) still do not provide useable information to the indicia decoder 114in order to detect or decode the truncated indicia 206. Nevertheless,the indicia seeds (referenced collectively as 304 b) may provide enoughuseful image data corresponding to the truncated indicia 206, that theuseful image data derived from the indicia seeds 304 b may be sufficientto accurately detect and decode the truncated indicia 206.

In order to perform these functions described in reference to FIGS. 1,3A, and 3B, the imaging device 100 may include multiple components inaddition to those previously described that are configured to interactwith and/or execute the various components described in, for example,FIG. 1 . In particular, FIG. 4 is a block diagram representative of anexample logic circuit capable of implementing, for example, the exampleimaging device 100 of FIG. 1 . The example logic circuit of FIG. 4 is aprocessing platform 400 capable of executing instructions to, forexample, implement operations of the example methods described herein,as may be represented by the flowcharts of the drawings that accompanythis description. Other example logic circuits capable of, for example,implementing operations of the example methods described herein includefield programmable gate arrays (FPGAs) and application specificintegrated circuits (ASICs).

The example processing platform 400 of FIG. 4 includes a processor 402such as, for example, one or more microprocessors, controllers, and/orany suitable type of processor. The example processing platform 400 ofFIG. 4 includes memory (e.g., volatile memory, non-volatile memory) 404accessible by the processor 402 (e.g., via a memory controller). Theexample processor 402 interacts with the memory 404 to obtain, forexample, machine-readable instructions stored in the memory 404corresponding to, for example, the operations represented by theflowchart(s) of this disclosure. Additionally, or alternatively,machine-readable instructions corresponding to the example operationsdescribed herein may be stored on one or more removable media (e.g., acompact disc (CD), a digital versatile disc (DVD), removable flashmemory, etc.) that may be coupled to the processing platform 400 toprovide access to the machine-readable instructions stored thereon. Theprocessor 402 and the memory 404 are disposed in the housing 102.

The example processing platform 400 of FIG. 4 includes one or morecommunication interfaces such as, for example, one or more networkinterfaces 406, and/or one or more input/output (I/O) interfaces 408disposed in the housing 102. The communication interface(s) may enablethe processing platform 400 of FIG. 4 to communicate with, for example,another device, system, host system (e.g., an inventory managementsystem, a POS station, etc.), datastore, database, and/or any othermachine.

The example processing platform 400 of FIG. 4 may include the networkinterface(s) 406 to enable communication with other machines (e.g., aninventory management system, a POS station, etc.) via, for example, oneor more networks. The example network interface(s) 406 include anysuitable type of communication interface(s) (e.g., wired and/or wirelessinterfaces) configured to operate in accordance with any suitablecommunication protocol(s). Example network interfaces 406 include aTCP/IP interface, a Wi-Fi™ transceiver (e.g., according to the IEEE802.11x family of standards), an Ethernet transceiver, a cellularnetwork radio, a satellite network radio, or any other suitableinterface based on any other suitable communication protocols orstandards.

The example, processing platform 400 of FIG. 4 may include theinput/output (I/O) interface(s) 408 (e.g., a Bluetooth® interface, anear-field communication (NFC) interface, a universal serial bus (USB)interface, a serial interface, an infrared interface, etc.) to (1)enable receipt of user input (e.g., from the trigger 120 of FIG. 1 , atouch screen, keyboard, mouse, touch pad, joystick, trackball,microphone, button, etc.), (2) communicate output data (e.g., modechange confirmations, visual indicators, instructions, data, images,etc.) to the user (e.g., via an output device 410, speaker, printer,haptic device, etc.), and/or (3) interact with other components of theprocessing platform 400 (e.g., a set of imaging components 412, theoutput device 410, etc.). Example output devices 410 may include a soundgeneration device, a haptic device, or the like.

To capture images of objects and/or barcodes on objects, the exampleprocessing platform 400 includes the set of imaging components 412disposed in the housing. The set of imaging components 412 includes theimaging assembly 106 under control of, for example, the processor 402 tocapture image frames representative of the portion of an environment inwhich the example imaging device 100 is operating that falls within theimaging FOV 108 of the set of imaging components 412. The imagingassembly 106 includes a plurality of photosensitive elements forming asubstantially flat surface. The processor 402 may be communicativelycoupled to the set of imaging components 412 via the input/output (I/O)interface(s) 408.

The example set of imaging components 412 includes any number and/ortype(s) indicia decoders 114 (e.g., the indicia decoder 114) to detectand/or decode indicia to determine the payload of the indicia. In someaspects, the indicia decoder 114 is implemented by the processor 402.The indicia decoder 114, e.g., via the processor 402, conveys thepayload of decoded indicia to a host system via a communicationinterface such as the network interface(s) 406 and/or the I/Ointerface(s) 408.

The example set of imaging components 412 includes an optical assembly414 to form images of objects in the FOV 108 on the surface of theimaging assembly 106. The optical assembly 414 may include any numberand/or type(s) of optical elements and/or components 414A including, forexample, one or more lenses, filters, focus motors, apertures, lensholder, liquid lenses, or any other components and/or optical elements.Moreover, to focus the set of imaging components 412 on an object, theexample set of imaging components 412 may include a focus controller412A, and the optical assembly 414 may include any number and/or type(s)of focus components 414B (e.g., motors, liquid lenses, etc.). In someaspects, the focus controller 412A is implemented by the processor 402.In certain aspects, the example set of imaging components 412 is afixed-focus scanner.

To illuminate a target to be imaged, the example set of imagingcomponents 412 may include the illumination generator 412B. Theillumination generator 412B may emit light in the FOV 108 to, forexample, facilitate autofocusing and/or improve the quality of imageframes captured by the imaging assembly 106.

Further, the set of imaging components 412 may include the search regiongenerator 122 and the distance calculator 123. As previously described,the search region generator 122 may be configured to generate a searchregion (e.g., example search regions 202, 302) within an image capturedby the imaging assembly 106, and to populate the search region withsearch seeds (e.g., search seeds 204, 304) that each represent areaswithin the captured image that may contain image data corresponding toan indicia (e.g., truncated indicia 206). The distance calculator 123may generally calculate a distance value (e.g., in centimeters, meters,inches, feet, etc.) indicating the distance between the imaging device(e.g., imaging device 100) and a target object that features an indiciafor each new image captured by the imaging device. As previouslydiscussed, the distance calculator 123 may calculate the distance valuein any suitable manner, such as, for example, by a parallax calculationbased on known dimensions of an indicia, time of flight of a light pulseor other suitable signal, and/or any other suitable method(s) orcombinations thereof. In any event, both the search region generator 122and the distance calculator 123 may be or include instructions that areexecutable by the processor 402 in order to perform the correspondingfunctions.

FIG. 5 illustrates an example method 500 for improving indicia decodingwith an imaging device, in accordance with various embodiments of thepresent invention. It should be understood that, in certain embodiments,any of the blocks of the method 500 may be performed by any of theexample imaging device 100, the imaging assembly 106, the indiciadecoder 114, the search region generator 122, the distance calculator123, the processor(s) 202, and/or any other suitable device.

The method 500 includes searching, by an imaging device, a search regionwithin a current image for an indicia (block 502). The search region(e.g., search regions 202, 302) may include a plurality of search seeds(e.g., search seeds 204, 304). In certain aspects, a center of an aimingindicator (e.g., aiming indicator 109) is disposed in a center of thesearch region and the indicia is presumed to be at the center of theaiming indicator.

Further, in some aspects, each seed of the plurality of search seeds israndomly placed within the search region. For example, the search regiongenerator 122 may randomly place each seed of the plurality of searchseeds within the search region. However, as part of this randomizedplacement, the search seed generator 122 may still apply certainplacement criteria when placing the search seeds. Namely, the searchseed generator 122 may not place multiple search seeds over a singlelocation within the search region. Two search seeds may touch (e.g.,share a common border), but in general, each individual search seed mayinclude a unique location or set of locations (e.g., pixels) within thecaptured image featuring the indicia. In this manner, the indiciadecoder 114 may attempt to detect and/or decode the indicia withoutanalyzing duplicitous image data, and thereby saving processingresources and time.

The method 500 also includes attempting, by the imaging device, todecode the indicia within the search region by analyzing image datacorresponding to each seed of the plurality of search seeds (block 504).In certain aspects, the indicia is a barcode, and the method 500 furtherincludes attempting to decode the barcode within the search region byapplying a decoding algorithm to the image data from each seed. In theseaspects, the image data located within the barcode includes verticallines of the barcode, which enables the indicia decoder 114 todistinguish the characteristic features of the barcode. Thus, theindicia decoder 114 may analyze the image data from the search seedsplaced on the barcode using the decoding algorithm to detect thebarcode, and may also proceed to decode the barcode once it has beenidentified. In particular, the decoding algorithm may be an edgedetection algorithm. Additionally, or alternatively, the indicia may beany one-dimensional indicia (e.g., a barcode) a two-dimensional indicia(e.g., a quick response (QR) code) and/or any other suitable indicia orcombinations thereof. Moreover, the decoding algorithm may be anysuitable algorithm for decoding any of the suitable indicia, such as adecoding algorithm configured to identify specifically arranged blocksof a matrix barcode, and/or any other suitable algorithm or combinationsthereof.

In any event, the method 500 further includes determining whether or notthe indicia was successfully decoded (block 506). If the indicia wassuccessfully decoded (YES branch of block 506), then the method 500 mayterminate. However, if the indicia was not successfully decoded (NObranch of block 506), then the method 500 may proceed to block 508,where the imaging device may capture a subsequent image featuring theindicia. In particular, the method 500 may further include, responsiveto not decoding the indicia, capturing a subsequent image featuring theindicia (block 508). For example, the indicia decoder 114 may analyzeimage data from each of the plurality of search seeds, and may be unableto detect and/or decode the indicia. As a result, the indicia decoder114 may transmit a signal to the imaging assembly 106 that thedetection/decoding of the indicia was unsuccessful. In response, theimaging assembly 106 may automatically capture a subsequent image of thetarget object featuring the indicia. A user/operator may inadvertentlyand/or intentionally move the imaging device between the first imagecapture and the subsequent image capture, so the imaging device mayproceed to determine a new distance between the device and the targetobject in order to determine a new search region.

Namely, the method 500 also includes, adjusting, by the imaging device,the search region based on a distance between the imaging device and theindicia (block 510). For example, after the imaging assembly 106captures the subsequent image, the imaging assembly 106 may transmit asignal to the distance calculator 123 indicating that the distancebetween the imaging device and the indicia featured in the subsequentimage should be calculated in order to determine the search regionwithin the subsequent image. In response, the distance calculator 123may proceed to calculate the distance between the imaging device and theindicia within the subsequent image, and may transmit the distance tothe search region generator 122. Upon receipt of the distance, thesearch region generator 122 may adjust (e.g., decrease/increase) thedimensions of the search region and/or adjust the number of search seedspopulated within the adjusted search region relative to the prior searchregion based on the distance between the imaging device and the indiciacalculated by the distance calculator 123.

In certain aspects, and as previously described, adjusting the searchregion further includes reducing and/or increasing an area of the searchregion based on the distance between the imaging device and the indicia.Moreover, in some aspects, adjusting the search region further includesincreasing and/or decreasing a number of search seeds within the searchregion based on the distance between the imaging device and the indicia.

Of course, it should be understood that the search region size and/orsearch seed density of a subsequent search region corresponding to asubsequent image may not be based on the search region size and/orsearch seed density of a prior search region of a prior image. Thedistance calculator 123 and search region generator 122 may operate todetermine the search region size and search seed density purely as afunction of the distance between the imaging device and the indiciafeatured in the respective image, without comparing relative distances,search region sizes, search seed densities, and/or any other metricsbetween images. Thus, any description of a particular search region asrelatively smaller/larger and/or a particular search seed density asrelatively smaller/larger than another respective search region size orsearch seed density may not be the result of a comparison activelyperformed by any of the components referenced herein, but may simply bethe result of a change in the distance of the imaging device from theindicia between subsequent image captures.

Regardless, when the distance calculator 123 and search region generator122 have adjusted the search region for the subsequent image, the method500 may proceed to block 512, where the subsequent image is designatedas the current image. More specifically, the imaging device maydesignate the subsequent image as the current image in order to performthe actions associated with at least blocks 502-506 again with respectto the subsequent image. Accordingly, the method 500 may return to block502, where the imaging device may proceed to search the search regionwithin the subsequent image (e.g., the newly designated current image)for the indicia.

The method 500 may further include iteratively performing the actions ofblocks 502-512 until the imaging device decodes the indicia. Generally,the imaging device 100 may perform the actions of blocks 502-512 as manytimes as is necessary to successfully detect and decode the indicia. Forexample, the imaging device 100 may search the search region for theindicia, attempt to decode the indicia, and responsive to not decodingthe indicia, capture a subsequent image, adjust the search region, anddesignate the subsequent image as the current image 2, 3, 4, 5, and/orany other suitable number of times in order to successfully detect anddecode the indicia. However, in certain instances, the imaging device100 may be configured to stop iteratively performing the actions ofblock 502-512 when a certain threshold is reached indicating that theindicia simply may not be successfully detected/decoded from thecaptured image, and that a new captured image may be required.

To illustrate, and in certain aspects, after each iteration, the imagingdevice 100 may increase an iteration index. In these aspects, the method500 may include iteratively performing the actions of blocks 502-508until the imaging device 100 decodes the indicia or the imaging device100 determines that the iteration index exceeds an iteration indexthreshold. Moreover, responsive to the imaging device 100 determiningthat the iteration index exceeds the iteration index threshold, theimaging device 100 may display (e.g., by output device 410) a message toa user requesting a subsequent image featuring the indicia. In response,an operator may capture a subsequent image featuring the indicia (e.g.,at a shorter distance from the target object than the prior image), andthe imaging device 100 may proceed to perform the actions of block502-508 until either the indicia featured in the subsequent image isdetected/decoded and/or the iteration index exceeds the iteration indexthreshold.

In some aspects, the method 500 may include iteratively performing theactions of block 502-512 until the imaging device decodes the indicia orat least one of (i) the imaging device determines that the iterationindex exceeds an iteration index threshold, (ii) the imaging devicedetermines that a decoding time corresponding to the current imageexceeds a decoding time threshold, or (iii) the image data from eachseed in the plurality of search seeds is analyzed without detecting theindicia. For example, the indicia decoder 114 may only have apre-determined amount of time (e.g., decoding time threshold) in orderto successfully detect/decode the indicia before the image is discarded.In this example, the decoding time threshold may be any suitable lengthof time, such as several milliseconds, several seconds, and/or any othersuitable length of time. However, responsive to the imaging devicedetermining that the decoding time exceeds the decoding time threshold,or the image data is analyzed without detecting the indicia, the method500 may further include displaying, by the imaging device, a message toa user requesting another image featuring the indicia.

The above description refers to a block diagram of the accompanyingdrawings. Alternative implementations of the example represented by theblock diagram includes one or more additional or alternative elements,processes and/or devices. Additionally, or alternatively, one or more ofthe example blocks of the diagram may be combined, divided, re-arrangedor omitted. Components represented by the blocks of the diagram areimplemented by hardware, software, firmware, and/or any combination ofhardware, software and/or firmware. In some examples, at least one ofthe components represented by the blocks is implemented by a logiccircuit. As used herein, the term “logic circuit” is expressly definedas a physical device including at least one hardware componentconfigured (e.g., via operation in accordance with a predeterminedconfiguration and/or via execution of stored machine-readableinstructions) to control one or more machines and/or perform operationsof one or more machines. Examples of a logic circuit include one or moreprocessors, one or more coprocessors, one or more microprocessors, oneor more controllers, one or more digital signal processors (DSPs), oneor more application specific integrated circuits (ASICs), one or morefield programmable gate arrays (FPGAs), one or more microcontrollerunits (MCUs), one or more hardware accelerators, one or morespecial-purpose computer chips, and one or more system-on-a-chip (SoC)devices. Some example logic circuits, such as ASICs or FPGAs, arespecifically configured hardware for performing operations (e.g., one ormore of the operations described herein and represented by theflowcharts of this disclosure, if such are present). Some example logiccircuits are hardware that executes machine-readable instructions toperform operations (e.g., one or more of the operations described hereinand represented by the flowcharts of this disclosure, if such arepresent). Some example logic circuits include a combination ofspecifically configured hardware and hardware that executesmachine-readable instructions. The above description refers to variousoperations described herein and flowcharts that may be appended heretoto illustrate the flow of those operations. Any such flowcharts arerepresentative of example methods disclosed herein. In some examples,the methods represented by the flowcharts implement the apparatusrepresented by the block diagrams. Alternative implementations ofexample methods disclosed herein may include additional or alternativeoperations. Further, operations of alternative implementations of themethods disclosed herein may combined, divided, re-arranged or omitted.In some examples, the operations described herein are implemented bymachine-readable instructions (e.g., software and/or firmware) stored ona medium (e.g., a tangible machine-readable medium) for execution by oneor more logic circuits (e.g., processor(s)). In some examples, theoperations described herein are implemented by one or moreconfigurations of one or more specifically designed logic circuits(e.g., ASIC(s)). In some examples the operations described herein areimplemented by a combination of specifically designed logic circuit(s)and machine-readable instructions stored on a medium (e.g., a tangiblemachine-readable medium) for execution by logic circuit(s).

As used herein, each of the terms “tangible machine-readable medium,”“non-transitory machine-readable medium” and “machine-readable storagedevice” is expressly defined as a storage medium (e.g., a platter of ahard disk drive, a digital versatile disc, a compact disc, flash memory,read-only memory, random-access memory, etc.) on which machine-readableinstructions (e.g., program code in the form of, for example, softwareand/or firmware) are stored for any suitable duration of time (e.g.,permanently, for an extended period of time (e.g., while a programassociated with the machine-readable instructions is executing), and/ora short period of time (e.g., while the machine-readable instructionsare cached and/or during a buffering process)). Further, as used herein,each of the terms “tangible machine-readable medium,” “non-transitorymachine-readable medium” and “machine-readable storage device” isexpressly defined to exclude propagating signals. That is, as used inany claim of this patent, none of the terms “tangible machine-readablemedium,” “non-transitory machine-readable medium,” and “machine-readablestorage device” can be read to be implemented by a propagating signal.

In the foregoing specification, specific embodiments have beendescribed. However, one of ordinary skill in the art appreciates thatvarious modifications and changes can be made without departing from thescope of the invention as set forth in the claims below. Accordingly,the specification and figures are to be regarded in an illustrativerather than a restrictive sense, and all such modifications are intendedto be included within the scope of present teachings. Additionally, thedescribed embodiments/examples/implementations should not be interpretedas mutually exclusive, and should instead be understood as potentiallycombinable if such combinations are permissive in any way. In otherwords, any feature disclosed in any of the aforementionedembodiments/examples/implementations may be included in any of the otheraforementioned embodiments/examples/implementations.

The benefits, advantages, solutions to problems, and any element(s) thatmay cause any benefit, advantage, or solution to occur or become morepronounced are not to be construed as a critical, required, or essentialfeatures or elements of any or all the claims. The claimed invention isdefined solely by the appended claims including any amendments madeduring the pendency of this application and all equivalents of thoseclaims as issued.

Moreover, in this document, relational terms such as first and second,top and bottom, and the like may be used solely to distinguish oneentity or action from another entity or action without necessarilyrequiring or implying any actual such relationship or order between suchentities or actions. The terms “comprises,” “comprising,” “has”,“having,” “includes”, “including,” “contains”, “containing” or any othervariation thereof, are intended to cover a non-exclusive inclusion, suchthat a process, method, article, or apparatus that comprises, has,includes, contains a list of elements does not include only thoseelements but may include other elements not expressly listed or inherentto such process, method, article, or apparatus. An element proceeded by“comprises . . . a”, “has . . . a”, “includes . . . a”, “contains . . .a” does not, without more constraints, preclude the existence ofadditional identical elements in the process, method, article, orapparatus that comprises, has, includes, contains the element. The terms“a” and “an” are defined as one or more unless explicitly statedotherwise herein. The terms “substantially”, “essentially”,“approximately”, “about” or any other version thereof, are defined asbeing close to as understood by one of ordinary skill in the art, and inone non-limiting embodiment the term is defined to be within 10%, inanother embodiment within 5%, in another embodiment within 1% and inanother embodiment within 0.5%. The term “coupled” as used herein isdefined as connected, although not necessarily directly and notnecessarily mechanically. A device or structure that is “configured” ina certain way is configured in at least that way, but may also beconfigured in ways that are not listed.

The Abstract of the Disclosure is provided to allow the reader toquickly ascertain the nature of the technical disclosure. It issubmitted with the understanding that it will not be used to interpretor limit the scope or meaning of the claims. In addition, in theforegoing Detailed Description, it can be seen that various features aregrouped together in various embodiments for the purpose of streamliningthe disclosure. This method of disclosure is not to be interpreted asreflecting an intention that the claimed embodiments require morefeatures than are expressly recited in each claim. Rather, as thefollowing claims reflect, inventive subject matter may lie in less thanall features of a single disclosed embodiment. Thus, the followingclaims are hereby incorporated into the Detailed Description, with eachclaim standing on its own as a separately claimed subject matter.

1. A method for improving indicia decoding with an imaging device, themethod comprising: (a) searching, by an imaging device, a search regionwithin a current image for an indicia, wherein the search regionincludes a plurality of search seeds; (b) attempting, by the imagingdevice, to decode the indicia within the search region by analyzingimage data corresponding to each seed of the plurality of search seeds;(c) responsive to not decoding the indicia, capturing, by the imagingdevice, a subsequent image featuring the indicia; (d) adjusting, by theimaging device, the search region based on a distance between theimaging device and the indicia featured in the subsequent image; (e)designating the subsequent image as the current image; and (f)iteratively performing (a)-(f) until the imaging device decodes theindicia.
 2. The method of claim 1, wherein adjusting the search regionfurther includes reducing or increasing an area of the search regionbased on the distance.
 3. The method of claim 1, wherein adjusting thesearch region further includes increasing or decreasing a number ofsearch seeds within the search region based on the distance.
 4. Themethod of claim 1, wherein a center of an aiming indicator is disposedin a center of the search region and the indicia is presumed to be atthe center of the aiming indicator.
 5. The method of claim 1, whereinthe indicia is a barcode, and the method further comprises: attemptingto decode the barcode within the search region by applying a decodingalgorithm to the image data from each seed.
 6. The method of claim 1,wherein after each iteration, the imaging device increases an iterationindex, and wherein the method further comprises: (f) iterativelyperforming (a)-(f) until the imaging device decodes the indicia or atleast one of (i) the imaging device determines that the iteration indexexceeds an iteration index threshold, (ii) the imaging device determinesthat a decoding time corresponding to the current image exceeds adecoding time threshold, or (iii) the image data from each seed in theplurality of search seeds is analyzed without detecting the indicia. 7.The method of claim 6, further comprising: responsive to the imagingdevice determining that the iteration index exceeds the iteration indexthreshold, the decoding time exceeds the decoding time threshold, or theimage data is analyzed without detecting the indicia, displaying, by theimaging device, a message to a user requesting another image featuringthe indicia.
 8. The method of claim 1, wherein each seed of theplurality of search seeds is randomly placed within the search region.9. An imaging device for improving indicia decoding, the devicecomprising: an imaging assembly configured to capture a current imagefeaturing an indicia, the current image comprising a set of image data;one or more processors; and a non-transitory computer-readable memorycoupled to the imaging assembly and the one or more processors, thememory storing instructions thereon that, when executed by the one ormore processors, cause the one or more processors to: (a) search asearch region within the image for the indicia, wherein the searchregion includes a plurality of search seeds, (b) attempt to decode theindicia within the search region by analyzing image data from the set ofimage data that corresponds to each seed of the plurality of searchseeds, (c) responsive to not decoding the indicia, cause the imagingassembly to capture a subsequent image featuring the indicia, (d) adjustthe search region based on a distance between the imaging device and theindicia featured in the subsequent image, (e) designate the subsequentimage as the current image, and (f) iteratively perform (a)-(f) untilthe indicia is decoded.
 10. The imaging device of claim 9, wherein theinstructions, when executed by the one or more processors, further causethe one or more processors to: adjust the search region by reducing orincreasing an area of the search region based on the distance.
 11. Theimaging device of claim 9, wherein the instructions, when executed bythe one or more processors, further cause the one or more processors to:adjust the search region by increasing or decreasing a number of searchseeds within the search region based on the distance.
 12. The imagingdevice of claim 9, further comprising: a distance calculator configuredto calculate the distance between the imaging device and the indiciabased on at least one of (i) an aiming indicator that is centered on theindicia or (ii) an emitted light pulse that propagates between theimaging device and the indicia.
 13. The imaging device of claim 9,wherein the indicia is a barcode, and the instructions, when executed bythe one or more processors, further cause the one or more processors to:attempt to decode the barcode within the search region by applying adecoding algorithm to the image data corresponding to each seed.
 14. Theimaging device of claim 9, wherein after each iteration, the one or moreprocessors increase an iteration index, and the instructions, whenexecuted by the one or more processors, further cause the one or moreprocessors to: (f) iteratively perform (a)-(f) until the indicia isdecoded or at least one of (i) the one or more processors determine thatthe iteration index exceeds an iteration index threshold, (ii) the oneor more processors determine that a decoding time corresponding to thecurrent image exceeds a decoding time threshold, or (iii) the image datafrom each seed in the plurality of search seeds is analyzed withoutdetecting the indicia.
 15. The imaging device of claim 14, wherein theinstructions, when executed by the one or more processors, further causethe one or more processors to: responsive to determining that theiteration index exceeds the iteration index threshold, the decoding timeexceeds the decoding time threshold, or the image data is analyzedwithout detecting the indicia, display a message to a user requestinganother image featuring the indicia.
 16. A tangible machine-readablemedium comprising instructions for improving indicia decoding, whenexecuted, cause a machine to at least: (a) search a search region withina current image for an indicia, wherein the search region includes aplurality of search seeds; (b) attempt to decode the indicia within thesearch region by analyzing image data that corresponds to each seed ofthe plurality of search seeds; (c) responsive to not decoding theindicia, capture a subsequent image featuring the indicia; (d) adjustthe search region based on a distance from the indicia featured in thesubsequent image; (e) designate the subsequent image as the currentimage; and (f) iteratively perform (a)-(f) until the indicia is decoded.17. The tangible machine-readable medium of claim 16, wherein theinstructions, when executed, further cause the machine to at least:adjust search region by reducing or increasing an area of the searchregion based on the distance.
 18. The tangible machine-readable mediumof claim 16, wherein the instructions, when executed, further cause themachine to at least: adjust the search region by increasing ordecreasing a number of search seeds within the search region based onthe distance.
 19. The tangible machine-readable medium of claim 16,wherein the indicia is a barcode, and the instructions, when executed,further cause the machine to at least: attempt to decode the barcodewithin the search region by applying a decoding algorithm to the imagedata corresponding to each seed.
 20. The tangible machine-readablemedium of claim 16, wherein after each iteration, the instructions, whenexecuted, further cause the machine to at least increase an iterationindex, and: (f) iteratively perform (a)-(f) until the indicia is decodedor at least one of (i) the iteration index exceeds an iteration indexthreshold, (ii) a decoding time corresponding to the current imageexceeds a decoding time threshold, or (iii) the image data from eachseed in the plurality of search seeds is analyzed without detecting theindicia; and responsive to determining that the iteration index exceedsthe iteration index threshold, the decoding time exceeds the decodingtime threshold, or the image data is analyzed without detecting theindicia, display a message to a user requesting another image featuringthe indicia.